Predicting Consistency-Maintenance Requirement of Code Clonesat Copy-and-Paste Time

Abstract

Abstract-Code clones have always been a double edged sword in software development. On one hand, it is a very convenient way to reuse existing code, and to save coding effort. On the other hand, since developers may need to ensure consistency among cloned code segments, code clones can lead to extra maintenance effort and even bugs. Recently studies on the evolution of code clones show that only some of the code clones experience consistent changes during their evolution history. Therefore, if we can accurately predict whether a code clone will experience consistent changes, we will be able to provide useful recommendations to developers on leveraging the convenience of some code cloning operations, while avoiding other code cloning operations to reduce future consistency maintenance effort. In this paper, we define a code cloning operation as consistency-maintenance-required if its generated code clones experience consistent changes in the software evolution history, and we propose a novel approach that automatically predicts whether a code cloning operation requires consistency maintenance at the time point of performing copy-and-paste operations. Our insight is that whether a code cloning operation requires consistency maintenance may relate to the characteristics of the code to be cloned and the characteristics of its context. Based on a number of attributes extracted from the cloned code and the context of the code cloning operation, we use Bayesian Networks, a machine-learning technique, to predict whether an intended code cloning operation requires consistency maintenance. We evaluated our approach on four subjects -two large-scale Microsoft software projects, and two popular open-source software projects -under two usage scenarios: 1) recommend developers to perform only the cloning operations predicted to be very likely to be consistency-maintenance-free, and 2) recommend developers to perform all cloning operations unless they are predicted very likely to be consistency-maintenance-required. In the first scenario, our approach is able to recommend developers to perform more than 50% cloning operations with a precision of at least 94% in the four subjects. In the second scenario, our approach is able to avoid 37% to 72% consistency-maintenance-required code clones by warning developers on only 13% to 40% code clones, in the four subjects.

Automatic Clone Recommendation for Refactoring Based on the Present and the Past

“…Cross-Version Clone Linking. We used an existing approach [52] to link the clone groups detected in different sampled versions, in order to restore the clone evolution history. This approach matches clones across versions based on the code location and textual similarity.…”

An empirical study on how project context impacts on code cloning

“…Recent studies on the evolution of code clones show that only some of the code clones change consistently during the evolution of the system. Wang et al analyze how to accurately predict whether a code clone will undergo consistent changes. The work, therefore, provides useful recommendations to developers on leveraging the convenience of some code cloning operations while avoiding other code cloning operations in order to reduce a future consistency maintenance effort.…”

Improving Maintenance-Consistency Prediction During Code Clone Creation

“…Currently, in order to avoid such defects, developers need to examine the corresponding code clones individually and determine if consistent changes need to be exerted on them every time when one of them is changed. Ideally, some tools that can assist developers in determining the need for consistent changes will help save software maintenance cost [7], [8].…”

“…With this knowledge, developers can re-think if they would like to perform the clone creation, thus improving development efficiency. Pioneering in this exploration of predicting clone-consistency-requirement is the work done by Wang et al [7]. In their work, Wang et al predict clone consistency by considering three attribute sets, drawing from the following three perspectives: history, code, and context.…”

“…The historical attributes from Wang et al's work are not really for clone creating instance; rather, they record changes of the files that include code clones before the copy-and-paste operation. Moreover, their investigation into historical attributes indicates that it is feasible to use only code attributes and context attributes to predict clone consistency [7].…”